视觉化量子电路概率:估计量子状态复杂性用于量子程序合成
Bao Gia Bach1,2, Akash Kundu2,3,4, Tamal Acharya2
1Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology, Ho Chi Minh City 70000, Vietnam.
Entropy (Basel, Switzerland)
|May 27, 2023
概括
本研究探讨了布尔和量子电路中的算法概率,定义状态概率和比较门集. 它分析了可访问性和可表达性,为量子机器学习和人工智能提供了洞察力.
科学领域:
- 理论计算机科学 理论计算机科学
- 量子信息科学 量子信息科学
- 算法概率 算法概率是指算法的概率.
背景情况:
- 算法概率为分析计算复杂性提供了一个框架.
- 布尔和量子组合逻辑电路是计算中的基本模型.
- 了解状态概率对于电路分析至关重要.
研究的目的:
- 将算法概率概念应用于布尔和量子电路.
- 定义和分析电路模型中状态的概率.
- 在有限的环境中研究门套的可达性和可表达性.
主要方法:
- 审查统计,算法,计算和电路复杂性之间的关系.
- 在电路计算模型中定义状态概率.
- 对比经典和量子门集的特征性属性.
- 在时空边界中列举和可视化可达性和可表达性.
主要成果:
- 电路模型中状态概率的确定的定义.
- 对比经典和量子门集,识别特征集.
- 量化和可视化可达性和可表达性为选定的门组.
- 分析了有关计算资源,普遍性和量子行为的结果.
结论:
- 该研究提供了量子和布尔电路中状态概率的基础分析.
- 这些发现为计算资源,普遍性和量子行为提供了洞察力.
- 突出了几何量子机器学习,量子算法合成和量子人工通用智能的潜在好处.
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